Moving body recognition system

ABSTRACT

Using communication unit positional information acquired using infrastructure communication and moving body positional information detected using millimeter-wave radar, a moving body existing in a blind spot of a radar detection region is recognized, and behavior is predicted from movement information of the moving body, by deleting the moving body information detected by millimeter-wave radar from the communication unit information acquired using infrastructure communication.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention relates to a moving body recognition system thatrecognizes a moving body such as a vehicle or pedestrian.

Description of the Related Art

With automatic driving of a vehicle or preventive safety technology asan object, acquisition of information for avoiding collision with avehicle or pedestrian is carried out utilizing acquisition of visualinformation using a camera or the like, detection of a moving body usinga sensor such as infrared radar or millimeter-wave radar, or acommunication network (hereafter referred to as infrastructurecommunication), such as a device that communicates between vehicles(hereafter referred to as inter-vehicle) or a communication deviceinstalled on a roadside or the like (a roadside unit) and a vehiclecommunication device (hereafter referred to as road-to-vehicle).

For example, detection of a moving body using millimeter-wave radar issuch that distinguishing of the position and category of a moving bodyis carried out by the millimeter-wave radar being directed in apredetermined direction and transmitted, and reflected waves from amoving body existing in that direction being detected, measured, andanalyzed. The position of the moving body is detected by the delay timebetween transmitted millimeter waves and received millimeter waves, orthe like, while the category of the moving body is distinguished bydistinguishing the strength of electric waves reflected from the movingbody. When attenuation of the reflected electric waves is small incomparison with the transmitted electric waves, the moving body is seento be a strongly reflecting moving body and thus determined to be avehicle, while when the reflected electric waves are weak electricwaves, the moving body is determined to be a human body.

Also, infrastructure communication such as inter-vehicle orroad-to-vehicle is such that acquisition of information on the position,velocity, and the like, of another vehicle, a pedestrian, or the like,is carried out in accordance with electric waves output from a roadsideunit, another vehicle, or a portable terminal possessed by a pedestrianor the like, using dedicated short range communications (DSRC) or thelike.

Furthermore, as positional information of a communication device mountedin a vehicle is information obtained from a global positioning system(GPS), the information includes a slight error, and the error is of asize that cannot be ignored with respect to the size of the vehicle,because of which there is technology whereby the existence of a vehiclewith which there is a danger of collision is more accurately recognizedby positional information of another vehicle being recognized by thecommunication device mounted in the vehicle, and the positionalinformation being corrected by information obtained by radar, asdisclosed in Patent Document 1.

Patent Document 1: Japanese Patent No. 4,569,652

As disclosed in Patent Document 1, being able to more accuratelyrecognize the existence of a vehicle with which there is a danger ofcollision by an error included in positional information of a vehicleacquired by infrastructure communication, with positional information ofa peripheral vehicle traveling in the same direction on a road withmultiple lanes as a target, being corrected by information obtained byradar, and a change in the position of the peripheral vehicle withrespect to the vehicle itself being estimated, is important inaccurately ascertaining the positional relationship of the peripheralvehicle to the vehicle itself.

However, information on a peripheral vehicle alone is not sufficientwith respect to a sudden appearance of a vehicle, pedestrian, or thelike, from a region forming a radar blind spot at a multiple ofintersections and the like existing in a road, and further improvementis needed as a way of avoiding collision.

SUMMARY OF THE INVENTION

The invention has an object of providing a moving body recognitionsystem for detecting a sudden appearance in a road of a vehicle,pedestrian, or the like.

A moving body recognition system of the invention includes a moving bodyposition detection unit that receives millimeter-wave radar wavesreflected from a moving body and detects radar detected positionalinformation of the moving body in a radar detection region, acommunication unit position detection unit that, using a signal from acommunication unit possessed by the moving body, detects positionalinformation of the communication unit, and a moving body recognitionunit that recognizes a moving body positioned in a blind spot of thedetection region by deleting information of the communication unithaving positional information near the moving body radar detectedpositional information detected by the moving body position detectionunit from information of the communication unit detected by thecommunication unit position detection unit.

According to the moving body recognition system of the invention, amoving body not detected by the moving body position detection unit issingled out from among moving bodies detected by the communication unitposition detection unit, and movement, that is, a sudden appearance, ofa moving body positioned in a region forming a millimeter-wave radarblind spot can be predicted by carrying out a prediction of the track ofthe moving body.

The foregoing and other objects, features, aspects, and advantages ofthe present invention will become more apparent from the followingdetailed description of the present invention when taken in conjunctionwith the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram showing an operational aspect of a moving bodyrecognition system of a first embodiment of the invention;

FIG. 2 is a block diagram showing a configuration of the moving bodyrecognition system of the first embodiment of the invention;

FIG. 3 is a diagram showing a state wherein communication units aredetected by the moving body recognition system of the first embodimentof the invention;

FIG. 4 is a diagram showing a state of traffic lights detected by themoving body recognition system of the first embodiment of the invention;

FIG. 5 is a schematic view representing a relationship between variablesrelating to a degree of coincidence;

FIG. 6 is a schematic view of a prediction vector; FIG. 7 is a flowchartshowing a process procedure for distinguishing a moving body using radarin the recognition system;

FIG. 8 is a flowchart showing a specific process procedure fordetermining sudden appearance in step S4 of FIG.

FIGS. 9A and 9B are schematic views indicating a case in which suddenappearance is determined; and

FIG. 10 is a flowchart showing a specific process procedure for changinga threshold in step S5 of FIG. 7.

DETAILED DESCRIPTION OF THE INVENTION First Embodiment Moving BodyRecognition System Operation Example

FIG. 1 shows a moving body recognition system operation example. FIG. 1shows a vehicle 1 about to enter an intersection and a pedestrian 2approaching the intersection. In this situation, due to an obstacle suchas a building, the pedestrian 2 cannot be seen from the vehicle 1 untilthe pedestrian 2 enters the intersection. Also, due to an obstacle suchas a building, the pedestrian 2 is in a blind spot of a detection regionof millimeter-wave radar included in the vehicle 1 until the pedestrian2 enters the intersection. A moving body recognition system including amillimeter-wave radar detection function and an infrastructurecommunication function is included in the vehicle 1, the pedestrian 2possesses a portable terminal including an infrastructure communicationfunction, and a roadside unit 3 including an infrastructurecommunication function is provided at the intersection.

In addition to moving body detection by millimeter-wave radar, themoving body recognition system included in the vehicle 1 carries outacquisition of a position and information of the pedestrian 2 from theportable terminal held by the pedestrian 2 using infrastructurecommunication, and acquisition of information on traffic light status,road signs, and past accident occurrence of peripheral roads from theroadside unit 3. Also, the moving body recognition system is configuredso as to carry out a distinguishing of the type of moving body and asudden appearance prediction at the same time as detecting a movingbody.

Moving Body Recognition System Configuration

The moving body recognition system mounted in the vehicle 1 of FIG. 1 isconfigured as shown in FIG. 2. That is, the moving body recognitionsystem includes an infrastructure communication unit 10 and a radardetection unit 11.

The infrastructure communication unit 10 is connected to a controllerarea network (CAN) through which vehicle information flows, receives asignal from an infrastructure communication unit included in anothervehicle, a portable terminal possessed by a pedestrian, or a roadsideunit installed on a road side, overhead line, or the like, and detectsthe position of a communication unit such as an infrastructurecommunication unit of another vehicle, a portable terminal of apedestrian, or a roadside unit using a communication unit positiondetection unit 12. Also, the infrastructure communication unit 10 isconnected to a road information acquisition unit 14, and is configuredso as to acquire road information provided by a roadside unit.

Also, the radar detection unit 11 receives reflections of millimeterwaves transmitted from an antenna (not shown) . Information from theradar detection unit 11 is sent to a moving body position detection unit15, and the position of a moving body is detected by transmittedmillimeter waves and received reflected waves being compared andprocessed in the moving body position detection unit 15.

The moving body position detection unit 15, communication unit positiondetection unit 12, and road information acquisition unit 14 areconnected to a communication bus 20, and the configuration is such thatinformation output by the moving body position detection unit 15,communication unit position detection unit 12, and road informationacquisition unit 14 is utilized in determining whether or not a movingbody has a bearing on the travel of the vehicle itself.

The moving body position detection unit 15 distinguishes between astationary object and a moving body from a temporal change in reflectedmillimeter waves, detects the position of a moving body, and outputsmoving body radar detected positional information. That is, the movingbody position detection unit 15 divides reflected waves into reflectedwaves that change together with time and reflected waves that do notchange, treats reflected waves that do not change as backgroundinformation, and treats reflected waves that change as reflected wavesfrom a moving body. Also, the moving body position detection unit 15detects not only the position of a moving object, but also detectsinformation on the amplitude of reflected waves.

The communication unit position detection unit 12 detects positionalinformation of communication units existing in all directions in thevehicle periphery. That is, using wireless communication, thecommunication unit position detection unit 12 detects positionalinformation of a communication unit mounted in a peripheral vehicle anda communication unit possessed by the pedestrian 2 from infrastructure,including from a region in a millimeter-wave radar blind spot such asbehind a building, and the like, and outputs the communication unitpositional information. Positional information of a communication unitmounted in a vehicle or a communication unit possessed by a pedestriancan be acquired by wireless communication with the communication unit.Also, the infrastructure communication unit 10 can acquire communicationunit positional information via the roadside unit 3.

A moving body recognition unit 100 is connected to the communication bus20. The moving body recognition unit 100 is configured to include amoving body identification unit 16, a coincidence rate calculation unit17, a behavior prediction unit 13, and a sudden appearance probabilitycalculation unit 18.

The coincidence rate calculation unit 17 receives communication unitpositional information obtained using infrastructure communication fromthe communication unit position detection unit 12, and moving body radardetected positional information obtained using millimeter-wave radarfrom the moving body position detection unit 15, and calculates thecoincidence rate of the moving body radar detected positionalinformation and communication unit positional information.

Generally, moving body radar detected positional information andcommunication unit positional information are slightly non-coinciding.Because of this, an error range is set as a threshold, anddistinguishing between coinciding and differing communication unitpositional information and moving body radar detected positionalinformation is carried out from positional information and movementinformation. Further, a communication unit with positional informationsuch that there is communication unit positional information obtainedusing infrastructure communication, but movement body radar detectedpositional information cannot be obtained, is extracted as a target foraction.

Positional information of the communication unit position detection unit12 is such that communication units are in two states, as indicated by Aand B in FIG. 3. A communication unit position indicated by A in FIG. 3is in a radar detection region blind spot, while the position of acommunication unit indicated by B in FIG. 3 indicates the position of acommunication unit that is in a radar detection region. However, thiscannot be distinguished simply from positional information of thecommunication unit position detection unit 12. Because of this, thecoincidence rate of the moving body radar detected positionalinformation and communication unit positional information is calculated,whereby positional information of a communication unit A positioned in aradar detection region blind spot can be ascertained. The communicationunit A positioned in a radar detection region blind spot obtained hereis treated as a monitoring target.

Some of the communication units shown as A in FIG. 3 appear directly infront of the vehicle itself, entering the radar detection region. Adetection state of a communication unit positioned in a blind spot ofthe radar detection region is as shown in FIG. 4. That is, an upperlevel of FIG. 4 represents a state of detecting communication unitpositional information obtained using infrastructure communication,while a lower level represents a state of detecting moving body radardetected positional information obtained using millimeter-wave radar,and the elapse of time is represented on the horizontal axis.

That is, when the vehicle itself approaches a communication unitpositioned in a blind spot of the radar detection region and enters aregion in which communication unit positional information obtained usinginfrastructure communication is detected, a detection value starts up.

As opposed to this, a moving body that is a target is in a blind spot ofthe detection region when using millimeter-wave radar, because of whichthe detection value does not start up, and the moving body is treated asnot being a problem. Then, the moving body appears in front of the eyesfrom the blind spot, the detection value suddenly starts up, and asudden response to the sudden appearance of a problematic moving body isrequired.

Herein, when all communication unit positional information obtainedusing infrastructure communication is taken as a target, the amount ofinformation is large, and time is needed to process the information. Inthis embodiment, a moving body positioned in a blind spot is singledout, and a sudden appearance prediction is carried with only this movingbody as a target, whereby the amount of information processing isreduced as far as possible, and the response can be quickened.

The coincidence rate of the moving body radar detected positionalinformation and communication unit positional information is calculatedusing the numerals shown in FIG. 5. Taking an infrastructurecommunication prediction region to be a circle with central coordinatesA (x0, y0) and radius D, and positional coordinates detected by radar tobe B (x1, y1), a value obtained by the value of a distance of a linesegment AB divided by the radius D being subtracted from 1 is defined asa coincidence rate (R).

Therefore, the coincidence rate is calculated as below.

Coincidence rate: R=1−(AB/D)

A: central coordinates of infrastructure communication prediction region

B: radar detection position

D: infrastructure communication prediction radius

The moving body identification unit 16 can distinguish between vehicleand pedestrian categories by acquiring reflected wave amplitudeinformation obtained using millimeter-wave radar output from the movingbody position detection unit 15, acquiring the coincidence rate from thecoincidence rate calculation unit 17, and changing a moving bodyidentification amplitude threshold.

In the event that a moving body category when using infrastructurecommunication is a mobile telephone or the like possessed by apedestrian, the threshold is changed as below.

th1=th0×(1+R)

th1: threshold after change

th0: threshold before change

R: coincidence rate

Meanwhile, when a moving body category when using infrastructurecommunication is a communication unit mounted in a vehicle, thethreshold is changed as below.

th1=th0×(1−R)

The behavior prediction unit 13 acquires the velocity of the vehicleitself from the CAN or the like of the vehicle itself, acquirespositional information of an object detected outside the millimeter-waveradar detection region, that is, a communication unit positioned in amillimeter-wave radar blind spot, from the communication unit positiondetection unit 12, predicts the next movement destination from pastpositional information, and represents the movement destination using aprediction vector.

Taking an i^(th) past velocity vector to be X_(i), an i^(th) weightingconstant to be A_(i), and a constant indicating up to which item of datais to be used to be N, a first prediction vector Y, which is a latestposition, is defined as below.

Y=1/NΣ ₁ ^(N)(A _(i) ×X _(i))   Math 1

Note that (N≧1)

The parameter A_(i) can be set at an optional value.

Herein, by the latest weighting constant A_(i) being greater than a pastweighting constant, calculation is carried out so that the effect of thelatest prediction vector is large, and the sudden appearance probabilitycan be raised swiftly even in response to sudden behavior of anothervehicle or a pedestrian.

An example of a prediction vector of a moving body acquired usinginfrastructure communication is shown in FIG. 6. The prediction vector Yis such that each of velocity vectors X1, X2, and X3 until reaching thelatest position is weighted and added, and the average thereofcalculated, because of which the next behavior can be expressed as avector from the latest position.

The road information acquisition unit 14 acquires information on theexistence of peripheral traffic lights or road signs, and information onwhether or not past accidents have occurred, and the like, usingwireless communication from infrastructure such as the roadside unit 3installed in the vicinity of a road, such as at an intersection.

Moving Body Distinguishing Process Procedure

FIG. 7 shows a flowchart of a moving body distinguishing process. Theflowchart of FIG. 7 represents a processing of moving body radardetected positional information obtained using millimeter-wave radar.Step S1 indicates that the radar detection unit 11 emits millimeter-waveradar, and that the moving body position detection unit 15 calculatesthe position of a moving body in accordance with returning reflectedradar waves reflected from the moving body. Step S2 indicates that themoving body position detection unit 15 carries out an increase of theamplitude of the reflected radar waves.

The moving body identification unit 16 determines whether or not amoving body that is a vehicle or pedestrian exists in step S3, confirmswhether the millimeter-wave radar system including the radar detectionunit 11 is to end in step S11 if no moving body is detected, and carriesout radar detection in step S1 again if the system is not to end.Meanwhile, if the system is to end, the moving body identification unit16 ends the process.

If a moving body is detected in step S3, the process of themillimeter-wave radar system including the radar detection unit 11proceeds to step S4.

In step S4, a sudden appearance determination process is carried out.Details are shown in FIG. 8.

In step S5, an amplitude change process is carried out. Details areshown in FIG. 10.

Continuing, the amplitude of the reflected waves and a threshold arecompared in step S6, and if the amplitude of the reflected waves isgreater than the threshold, the moving body identification unit 16distinguishes the category of the moving body as a vehicle in step S7.Meanwhile, if the amplitude of the reflected waves is smaller than thethreshold, the moving body identification unit 16 distinguishes thecategory as a pedestrian in step S8. Reflection from a pedestrian isconsidered to be reflection from a large number of points, and thedistinguishing can be carried out by ascertaining reflectioncharacteristics in advance.

Continuing, steps from step S9 onward describe a process ofdistinguishing a bicycle.

Sudden Appearance Determination Process Procedure

As previously mentioned, FIG. 8 shows a flowchart of the suddenappearance determination process of step S4 in FIG. 7. In the flowchart,the coincidence rate calculation unit 17 calculates the coincidence ratein step S21. Then, it is determined in step S22 whether or not thecoincidence rate is greater than a threshold T, an object detected usingmillimeter-wave radar can be determined to be the same as an objectdetected using infrastructure communication if the coincidence rate isgreater than the threshold T, while if the coincidence rate is smallerthan the threshold T, it is determined that there is no object detectedusing millimeter-wave radar corresponding to an object detected usinginfrastructure communication. That is, an object among objects detectedusing infrastructure communication that is not detected usingmillimeter-wave radar can be singled out.

In step S23, the behavior prediction unit 13 predicts the path ofanother vehicle or a pedestrian from the positional information acquiredfrom the communication unit position detection unit 12, and representsthe prediction as a velocity vector. This velocity vector is taken to bea predicted path vector.

When there are a multiple of objects detected using infrastructurecommunication, the one with the highest coincidence rate is determinedto be the same as an object detected using millimeter-wave radar, thatis, the same as a moving body. Also, when there is an object detectedusing infrastructure communication in a position extremely near a movingbody with a high coincidence rate, determination of whether or not theobject is a target of the sudden appearance determination process iscarried out depending on whether or not the object is within themillimeter-wave radar detection region.

Meanwhile, if the coincidence rate is equal to or lower than thethreshold T in step S22, it is determined that an object detected is notthe same as an object detected using infrastructure communication.

Also, when there is no moving body radar detected positional informationcorresponding to communication unit positional information obtainedusing infrastructure communication, a communication unit detected by thecommunication unit position detection unit 12 of the infrastructurecommunication unit 10 is assumed to be positioned outside the radardetection region, and on the premise that the communication unit is amoving body that may suddenly appear, the process of the behaviorprediction unit 13 is carried out in accordance with a prediction vectorof a moving body acquired using infrastructure communication, asillustrated in FIG. 6.

If it is determined in step S22 that the coincidence rate is equal to orlower than the threshold T, the sudden appearance determination processis continued in accordance with the determination, and collision isavoided. Because of this, the millimeter-wave radar system including theradar detection unit 11 is such that there is no need for a collisionavoiding process to be newly carried out with respect to an object oncerecognized using infrastructure communication, even when a moving bodyappears in the radar detection region from a blind spot. By integratinginformation acquired using infrastructure communication and radardetected positional information obtained using millimeter-wave radar inthis way, the amount of information processing can be reduced.

In step S24, the behavior prediction unit 13 predicts the behavior ofthe vehicle itself, in the same way as predicting the path of anothervehicle or a pedestrian, from the track to date of the vehicle itselfacquired from the CAN or the like, and represents the prediction as avelocity vector. This velocity vector is taken to be a predicted pathvector.

In step S25, the behavior prediction unit 13 compares the predicted pathvector of another vehicle or a pedestrian calculated in step S23 and thepredicted path vector of the vehicle itself calculated in step S24, anddetermines that a sudden appearance of a moving body with respect to thevehicle itself will occur when the end point of the predicted pathvector of the other vehicle or pedestrian is within the certain radius Dfrom the end point of the predicted path vector of the vehicle itself,or when the two predicted path vectors intersect.

FIGS. 9A and 9B show examples of determining sudden appearance when theendpoints are near and when the prediction vectors intersect.

Also, when the behavior prediction unit 13 determines in step S25 thatsudden appearance will occur, the process divides at step S26, and thesudden appearance probability calculation unit 18 calculates the suddenappearance probability in step S27. The sudden appearance probability iscalculated in accordance with the distance between the end points of theprediction vector of the vehicle itself and the prediction vector of theother vehicle or pedestrian, and on whether or not the vectorsintersect.

The sudden appearance probability is defined below. When a distance ABbetween an end point A of the prediction vector of the vehicle itselfand an end point B of the prediction vector of the other vehicle orpedestrian is taken to be x and the radius of a hazardous area shown inFIG. 9A is taken to be d when the end points are near, as shown in FIG.9A, a sudden appearance probability Rc is

Rc=50 +50 ×(d−x)D

(no intersection of prediction vectors, and 0 <x <d)

D: infrastructure communication prediction radius.

Consequently, when the prediction vector of the vehicle itself and theprediction vector of the other vehicle intersect, as shown in FIG. 9B,the sudden appearance probability Rc is

Rc=100

(with intersection of prediction vectors).

The hazardous area radius d is set at an optional value as a parameter .When the value is large, it is easy to determine that there will be asudden appearance, but the reliability decreases.

Also, the road information acquisition unit 14 may acquire the hazardousarea radius d as road information from infrastructure.

Also, when the behavior prediction unit 13 does not determine in stepS25 that there will be a sudden appearance, the process divides at stepS26, and the sudden appearance probability calculation unit 18 ends bysetting the sudden appearance probability at 0 in step S28.

Threshold Change Process procedure

FIG. 10 shows a flowchart of a threshold change process. Continuing fromstep S4 in FIG. 7, a threshold change process of step S41 onward iscarried out. In step S41, the coincidence rate calculation unit 17calculates the coincidence rates of an object detected using radar andall objects detected using infrastructure communication, and searchesfor the object with the highest coincidence rate.

In the following step S42, the coincidence rate calculation unit 17confirms the moving body category of the object with the highestcoincidence rate detected using infrastructure communication. Then, ifthe category is a human in step S43, the moving body identification unit16 raises the amplitude threshold in accordance with the degree ofcoincidence in step S44, whereby the object is easily identified as ahuman. 6

Meanwhile, if the category is a vehicle in step S43, the moving bodyidentification unit 16 lowers the amplitude threshold in accordance withthe degree of coincidence instep S45, whereby the object is easilyidentified as a vehicle.

Sudden Appearance Determination Correction Process Procedure

(Traffic Light Information)

The road information acquisition unit 14 is configured so as to acquireinformation relating to the road environment in the periphery of thevehicle itself. That is, the road information acquisition unit 14acquires information on the lighting state of traffic lights and theexistence of road signs. Further, for example, when the lighting stateof a set of traffic lights in the vicinity of another vehicle or apedestrian is red when determining sudden appearance in step S25 in FIG.8, it is determined that there is a high possibility of the othervehicle or pedestrian stopping because of the traffic lights, and thesudden appearance probability is estimated to be low.

As one example, the sudden appearance probability Rc is corrected asbelow. Cr, Cy, and Cb indicate correction values when the lighting stateof a set of traffic lights in the vicinity of another vehicle or apedestrian is red, yellow, and green respectively. A sudden appearanceprobability Rc1 after correction shown below is calculated.

Rc1=Rc−Cr (when red)

Rc1=Rc−Cy (when yellow)

Rc1=Rc−Cb (when green)

The correction values Cr, Cy, and Cb can be set at optional values asparameters. By Cr when the lights are red being greater than Cy when thelights are yellow, the sudden appearance probability when a set oftraffic lights in the vicinity of another vehicle or a pedestrian is redis smaller than when the lights are yellow, and by Cb when the lightsare green being set close to 0, the degree of accuracy of the suddenappearance determination can be raised.

Also, the road information acquisition unit 14 may acquire settingvalues of the correction values Cr, Cy, and Cb using infrastructurecommunication.

Sudden Appearance Determination Correction Process Procedure

(Crossing Prohibited, Halt, Priority Road)

Road sign information to the effect that crossing of the road of thevehicle itself is prohibited, or that the road has a halt or is apriority road, or the like, is acquired by the road informationacquisition unit 14. When carrying out the sudden appearancedetermination of step S25 in FIG. 8, the coincidence rate calculationunit 17 determines that no pedestrian will cross, and estimates thesudden appearance probability to be low.

As one example, the sudden appearance probability Rc is corrected asbelow. Cs indicates a correction value in accordance with a road signsuch as crossing prohibited, halt, or priority road, and the suddenappearance probability Rc1 after correction is calculated using thefollowing equation.

Rc1=Rc−Cs (in the case of crossing prohibited, halt, or priority road).

The correction value Cs is set at an optional value as a parameter.Also, a setting value may be acquired by the road informationacquisition unit 14 using infrastructure communication.

Also, information on a halt or priority road is not necessarily onlyroad sign information, but also includes information painted on theroad.

Sudden Appearance Determination Correction Process Procedure (AccidentOccurrence Information)

Information on past sudden appearance accident occurrence and hazardousplaces is acquired by the road information acquisition unit 14. Whencarrying out the sudden appearance determination of step S25 in FIG. 8,the coincidence rate calculation unit 17 determines that a place ishazardous, and sets the sudden appearance probability to be high.

As one example, the sudden appearance probability Rc is corrected asbelow. Ca indicates an accident occurrence correction value when anaccident has occurred in the past, and the sudden appearance probabilityRc1 after correction is calculated using the following equation.

Rc1=Rc−Ca (when an accident has occurred).

Bicycle Distinguishing Process Procedure

When amplitude is within a certain range α, which is a threshold, andthe moving body identification unit 16 has difficulty in distinguishingbetween a vehicle and a pedestrian when comparing amplitude andthreshold in step S9 in FIG. 7, the moving body identification unit 16determines in step S10 that the moving body category is a bicycle.

The value α used in bicycle distinguishing is acquired by the movingbody identification unit 16 using infrastructure communication.

When the answer is “No” in step S9 in FIG. 7, and the system does notend in step S11, the radar detection of step S1 is carried out again.Meanwhile, when the system ends in step S11, the radar moving bodydistinguishing process of FIG. 7 ends.

According to the moving body recognition system of the first embodiment,as heretofore described, millimeter-wave radar moving bodydistinguishing wherein a vehicle and pedestrian are distinguishedbetween in accordance with the signal strength of reflected waves issuch that, using a result of infrastructure information detection, adistinguishing threshold is raised or lowered in accordance with thecoincidence rate with an object detected using infrastructureinformation, whereby the degree of detection accuracy can be increased.

Also, according to the first embodiment, the behavior of another vehicleor a pedestrian outside a millimeter-wave radar detection region isexpressed as a prediction vector, and a sudden appearance aftermillimeter-wave radar detection can be detected by calculating thedistance of the prediction vector from a prediction vector of thevehicle itself and whether or not the vectors intersect.

Also, according to the first embodiment, traffic light information isacquired from infrastructure, and when there is a factor causing themovement of a moving body to stop, such as a road in the vicinity ofanother vehicle or a pedestrian having a red light, the probability ofthe other vehicle or the pedestrian suddenly appearing is estimated tobe low, whereby the degree of accuracy of sudden appearance predictioncan be raised.

Also, traffic lights not being the only factor causing the movement of amoving body to stop, when crossing is prohibited at the location of apedestrian, or when there is a halt point on a road in the vicinity ofanother vehicle, the probability of the other vehicle or the pedestriansuddenly appearing is estimated to be low, whereby the degree ofaccuracy of sudden appearance prediction can be raised.

Also, priority road information is acquired from infrastructure such asa roadside unit installed at an intersection, and the probability ofanother vehicle or a pedestrian suddenly appearing is estimated to below when the vehicle itself is on a priority road, whereby the degree ofaccuracy of sudden appearance prediction can be raised.

Also, according to the first embodiment, information on accidentoccurrence is acquired from infrastructure such as a roadside unitinstalled at an intersection, and when the place is a road where anaccident has occurred in the past or where there is a danger of suddenappearance, the probability of another vehicle or a pedestrian suddenlyappearing is estimated to be high, whereby the degree of accuracy ofsudden appearance prediction can be raised.

Also, according to the first embodiment, when it is difficult todistinguish between a pedestrian and a vehicle simply from the signalstrength of reflected millimeter-wave radar waves, and when acquiringinformation from infrastructure distinguishing a moving body as apedestrian, the moving body is distinguished as a bicycle, whereby thedegree of accuracy of moving body distinguishing can be raised.

According to the first embodiment, a moving body positioned in a blindspot of a millimeter-wave radar detection region is recognized usingcommunication unit positional information, and moving bodies positionedin the millimeter-wave radar detection region are such that movingbodies taken as a target are limited by information near positionalinformation obtained by a moving body position detection unit usingmillimeter-wave radar being deleted. This reduction of moving bodyinformation, a prediction of moving body behavior, calculation of movingbody sudden appearance probability, and the like, are carried out by themoving body recognition unit 100.

Second Embodiment

In the first embodiment, the moving body recognition system is describedas being for mounting in a vehicle. The moving body recognition system,not being limited to mounting in a vehicle, can be provided in a systemthat provides road information, detect positional information of avehicle-mounted communication unit using infrastructure communication,and be utilized so as to provide information to a moving body with whichan encounter is envisaged. In particular, an information provisionsystem of a roadside unit is such that a sudden collision can beprevented by lighting of traffic lights for traffic control beingmanipulated in accordance with traffic conditions. A configuration andfunctions of the system are the same as in the first embodiment, inwhich the system is described as a vehicle-mounted system.

Various modifications and alterations of the invention will be apparentto those skilled in the art without departing from the scope and spiritof this invention, and it should be understood that this is not limitedto the illustrative embodiments set forth herein.

What is claimed is:
 1. A moving body recognition system, comprising: amoving body position detection unit that receives millimeter-wave radarwaves reflected from a moving body and detects radar detected positionalinformation of the moving body in a radar detection region; acommunication unit position detection unit that, using a signal from acommunication unit possessed by the moving body, detects positionalinformation of the communication unit; and a moving body recognitionunit that recognizes a moving body positioned in a blind spot of thedetection region by deleting information of the communication unithaving positional information near the moving body radar detectedpositional information detected by the moving body position detectionunit from information of the communication unit detected by thecommunication unit position detection unit.
 2. The moving bodyrecognition system according to claim 1, wherein the moving bodyposition detection unit, the communication unit position detection unit,and the moving body recognition unit are mounted in a vehicle.
 3. Themoving body recognition system according to claim 1, wherein the movingbody position detection unit, the communication unit position detectionunit, and the moving body recognition unit are provided in a system thatprovides road information.
 4. The moving body recognition systemaccording to claim 1, wherein the moving body recognition unit has acoincidence rate calculation unit, which calculates a coincidence rateof the moving body radar detected positional information detected by themoving body position detection unit and the communication unitpositional information acquired by the communication unit positiondetection unit, and a moving body identification unit that identifies acategory of the moving body, and changes a threshold when calculatingthe coincidence rate in accordance with a result of identification bythe moving body identification unit.
 5. The moving body recognitionsystem according to claim 1, wherein the moving body recognition unitincludes a behavior prediction unit that, from a track of positionalinformation of the communication unit existing outside the detectionregion of the moving body position detection unit, predicts behavior ofthe communication unit using a positional information prediction vectorof the communication unit.
 6. The moving body recognition systemaccording to claim 5, wherein the moving body recognition unit has asudden appearance probability calculation unit that calculates aprobability of the moving body suddenly appearing in accordance with thebehavior prediction unit, and when there is a factor causing the movingbody to stop in accordance with acquired road information, the suddenappearance probability calculated by the sudden appearance probabilitycalculation unit is estimated to be low.
 7. The moving body recognitionsystem according to claim 6, wherein the factor causing the moving bodyto stop is a road sign indicating that crossing is prohibited.
 8. Themoving body recognition system according to claim 6, wherein the factorcausing the moving body to stop is a road sign indicating a halt.
 9. Themoving body recognition system according to claim 6, wherein the factorcausing the moving body to stop is that a vehicle itself is on apriority road.
 10. The moving body recognition system according to claim5, wherein the moving body recognition unit has a sudden appearanceprobability calculation unit that calculates a probability of the movingbody suddenly appearing in accordance with the behavior prediction unit,and when acquired road information indicates a place where an accidentdue to sudden appearance has occurred or a dangerous place, the suddenappearance probability calculated by the sudden appearance probabilitycalculation unit is estimated to be high.
 11. The moving bodyrecognition system according to claim 4, wherein the moving bodyrecognition unit is such that when there is difficulty in distinguishingbetween a pedestrian and a vehicle from millimeter-wave radar reflectedwave strength, and a moving body is categorized as a pedestrian by thecommunication unit position detection unit, the moving body isdetermined to be a bicycle.